How to group documents by hour without day in elasticsearch? - elasticsearch

Question

i have a application who a survey is asked every day by users, and i want to have average answers hours. I tried some request but i can't group all documents by hours, it's grouped by hour by day..
I do this :
{
"aggs": {
"byHour": {
"date_histogram": {
"field": "date",
"interval": "hour",
"format" : "H"
}
}
}
}
}
It's wrapped by hour but also by date, and i want day as ignored.
[
{
"key_as_string": "0",
"key": 1533945600000,
"doc_count": 40,
"group_by_state": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": []
}
},
{
"key_as_string": "1",
"key": 1533949200000,
"doc_count": 345,
"group_by_state": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": []
}
},
{
"key_as_string": "23",
"key": 1534028400000,
"doc_count": 15,
"group_by_state": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": []
}
},
{
"key_as_string": "0",
"key": 1534032000000,
"doc_count": 0,
"group_by_state": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": []
}
},
{
"key_as_string": "1",
"key": 1534035600000,
"doc_count": 2,
"group_by_state": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": []
}
},
{
"key_as_string": "2",
"key": 1534039200000,
"doc_count": 3,
"group_by_state": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": []
}
}
]
Mapping of type
{
"myIndex": {
"mappings": {
"answer": {
"properties": {
"date": {
"type": "date"
},
"lang": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"level": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"offset": {
"type": "long"
},
"patientCaretrackId": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"protocolId": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"query": {
"properties": {
"constant_score": {
"properties": {
"filter": {
"properties": {
"bool": {
"properties": {
"must": {
"properties": {
"term": {
"properties": {
"questionId": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"questionnaireId": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
}
}
}
}
}
}
}
}
}
}
}
}
},
"questionId": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"questionnaireId": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"surgeonId": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"value": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
},
"fielddata": true
}
}
}
}
}
}
Example of documents :
[
{
"date": "2018-09-11T00:00:00.000Z",
"lang": "fr",
"level": "red",
"offset": 21,
"patientCaretrackId": "5b894b10a9f7afec73762113",
"protocolId": "ptg-koos-long-v1",
"questionnaireId": "j21",
"surgeonId": "699362de-f040-4799-b1ea-53f5b4a2fe03",
"value": "permanentes",
"questionId": "frequence-douleur-2"
},
{
"date": "2018-09-11T00:00:00.000Z",
"lang": "fr",
"level": "red",
"offset": 21,
"patientCaretrackId": "5b894b10a9f7afec73762113",
"protocolId": "ptg-koos-long-v1",
"questionnaireId": "j21",
"surgeonId": "699362de-f040-4799-b1ea-53f5b4a2fe03",
"value": "permanentes",
"questionId": "frequence-douleur-2"
}
]
It's possible to do this with an query Elasticsearch ?
Thank you,

Answer 1

You can use a terms aggregation with a script:
https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-terms-aggregation.html#search-aggregations-bucket-terms-aggregation-script
GET /_search
{
"aggs" : {
"hours" : {
"terms" : {
"script" : {
"source": "doc['date'].getHour()",
"lang": "painless"
}
}
}
}
}
(Just to give you an idea, not sure at all about the script itself ..)

Answer 2

I found thx
{
"size": 0,
"aggs": {
"byHour": {
"date_histogram": {
"field": "date",
"interval": "hour",
"format" : "H",
"keyed": true,
"time_zone": "+02:00"
}
}
}
}
The response :
{
"took": 9,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 2796,
"max_score": 0,
"hits": []
},
"aggregations": {
"byHour": {
"buckets": {
"17": {
"key_as_string": "17",
"key": 1536159600000,
"doc_count": 2006
},
"18": {
"key_as_string": "18",
"key": 1536163200000,
"doc_count": 790
}
}
}
}
}